M_Map: A mapping package for Matlab

You have collected your data, loaded it into Matlab , analyzed everything to death, and now you want to make a simple map showing how it relates to the world.

But you can't.

Instead you have to figure out how to save all your data, and then read it into another program (like, for example GMT ), and then spend all that extra time figuring out why it doesn't give you what you expected it would...or you can invest in Matlab's own mapping toolbox (with a similarly steep learning curve)... or not!

Announcing M_Map v1.4h! (updated Sep/2014)

M_Map is a set of mapping tools written for Matlab v5 and later. These include:
  1. Routines to project data in 19 different spherical projections (and determine inverse mappings)
  2. A grid generation routine to make nice axes with limits either in lat/long terms or in planar X/Y terms.
  3. A coastline database (with 1/4 degree resolution)
  4. A global elevation database (1 degree resolution)
  5. Hooks into freely available high-resolution coastline and bathymetry databases
New in release 1.4h are
  1. ETOPO2v2 and ETOPO1 support.
  2. Handled some warnings about BITMAX that arise in Matlab 2014b. Note - I have only been able to fix or workaround SOME of the really bad bugs in 2014b. Use with caution (or better yet don't use). EPS output in particular is really awful, even if the screen plot looks "nice". Fortunately mathworks "may consider fixing this in future releases".
  3. Added option to output national+state or national borders only in m_gshhs.
New in release 1.4g are
  1. m_ellipse.m to plot tidal ellipses (say, from T_Tide )
  2. Option to use either decimal-degrees or degrees/decimal-minutes in grid axis labels
  3. Matlab 2013b has a bad bug in the dataaspectratio axes property that affects pretty much everything graphical. This version of M_Map has a workaround that MOSTLY works, but it would be better to avoid using 2013b.
New in release 1.4f are
  1. m_shaperead.m to read SHAPEFILES! (so Natural Earth can be used for political boundaries instead of DCW, among other opportunities)
  2. gshhs version 2 support
  3. partial OCTAVE compatibility
New in release 1.4e are
  1. GSHHS Now comes with the WDB rivers and borders database, and links to them have been added via m_gshhs.m
  2. Ellipsoidal Albers and Lambert conic projections included
New in release 1.4d are
  1. Modifications to work around bugs in matlab7 contourf
  2. Robinson projection
  3. A few compatibility issues with current matlab versions
  4. Upgraded hooks into some databases.
New in release 1.4b are
  1. m_hatch for hatched and speckled patches
  2. old-fashioned speckled coastlines (good for B&W pics - see Example 13).
  3. m_lldist now also returns points on great circle geodesics.
  4. m_fdist, m_idist, and m_geodesic for geodesics on an ellipsoidal earth.
New in release 1.4 are
  1. m_pcolor
  2. m_coord (to allow for geographic and geomagnetic coordinate systems)
  3. A very few minor bug fixes.
  4. Some hints about and examples of adding satellite image data to your maps.

How to get M_Map

You can download the M_Map toolbox either as a gzipped tar-file , or as zip archive (Click on these links to download). If you are unpacking the zip file MAKE SURE YOU ALSO UNPACK SUBDIRECTORIES! Both are around 650k in size. Once you have this archive, read the Getting started section of the User's guide to correctly install this toolbox, and sections 9 and 10.1 to install TerrainBase and GSHHS respectively.

A number of examples have been given to highlight the various capabilities of M_Map (thumbnails are shown above). 

You can also get  m_namebox (a set of utilities for automatically adding names to your map),  through its home page at http://www.nersc.no/~even/ .

User's guide

  1. Getting started
  2. Specifying projections
    1. Azimuthal projections
    2. Cylindrical and Pseudo-cylindrical projections
    3. Conic projections
    4. Miscellaneous global projections
    5. Yeah, but which projection should I use?
    6. Map scales
    7. Map coordinate systems -geographic and geomagnetic
  3. Coastlines and Bathymetry
    1. Coastline options
    2. Topography/Bathymetry options
  4. Customizing the axes
    1. Grid lines and labels
    2. Titles and x/ylabels
    3. Legend Boxes 
    4. Scale bar 
  5. Adding your own data
    1. Drawing lines, text, arrows, patches, hatches, speckles, and contours
    2. Drawing images and p_color
    3. Drawing tracklines
    4. Drawing range rings and geodesics
    5. Converting longitude/latitude to projection coordinates
    6. Converting projection coordinates to longitude/latitude
    7. Computing distances between points 
  6. More complex plots
  7. Removing data from a plot
  8. Adding your own coastlines
    1. DCW political boundaries
    2. ESRI Shapefiles and Natural Earth political boundaries
  9. Adding your own topography/bathymetry
    1. Sandwell and Smith Bathymetry
  10. Using TerrainBase 5-minute or ETOPO 2- and 1- minute global bathymetry/topography
  11. Using the GSHHS high-resolution coastline database
    1. Installing GSHHS
    2. Using GSHHS effectively
  12. M_Map toolbox contents and description
  13. Known Problems and Bugs
  14. OCTAVE Compatibility Issues
  15. Changes since last release 
For information, help, suggestions, or bug reports, contact Rich Pawlowicz , ( rich@eos.ubc.ca )



 A number of people have helped out with suggestions, code fixes, etc.  I am especially grateful for the work done by E. Firing, D. Byrne,  M. Mann,  J. Pringle, and J. E. Nilsen who have all contributed code.


1. M_Map Logo

patch(.55*[-1 1 1 -1],.25*[-1 -1 1 1]-.55,'w');
set(gcf,'units','inches','position',[2 2 3 3]);
set(gcf,'paperposition',[3 3 3 3]);

2. Lambert Conformal Conic projection of North American Topography

m_proj('lambert','long',[-160 -40],'lat',[30 80]);
m_coast('patch',[1 .85 .7]);

3. Stereographic projection of North Polar regions

% Note that coastline is drawn OVER the grid because of the order in which
% the two routines are called

m_grid('xtick',12,'tickdir','out','ytick',[70 80],'linest','-');
m_coast('patch',[.7 .7 .7],'edgecolor','r');

4. Two Interrupted Projections of the World's Oceans

Slongs=[-100 0;-75 25;-5 45; 25 145;45 100;145 295;100 290];
Slats= [  8 80;-80  8; 8 80;-80   8; 8  80;-80   0;  0  80];
for l=1:7,
        'ytick',[-80:20:80],'yticklabels',[],'linest','-','color',[.9 .9 .9]);
xlabel('Interrupted Sinusoidal Projection of World Oceans');
% In order to see all the maps we must undo the axis limits set by m_grid calls:

Slongs=[-100 43;-75 20; 20 145;43 100;145 295;100 295];
Slats= [  0  90;-90  0;-90   0; 0  90;-90   0;  0  90];
for l=1:6,
 m_coast('patch',[.6 .6 .6]);
xlabel('Interrupted Mollweide Projection of World Oceans');

5. Oblique Mercator Projection with quiver and contour data

%% Nice looking data

m_proj('oblique','lat',[56 30],'lon',[-132 -120],'aspect',.8);

m_coast('patch',[.9 .9 .9],'edgecolor','none');
hold on;
xlabel('Simulated surface winds');

m_coast('patch',[.9 .9 .9],'edgecolor','none');
hold on;
xlabel('Simulated something else');

6. Miller Projection with Great Circle

% Plot a circular orbit

m_coast('color',[0 .6 0]);

7. Lambert Conformal Projection with high-resolution bathymetry of Western Mediterranean

m_proj('lambert','lon',[-10 20],'lat',[33 48]);

8. Demonstration of fancy vectors

m_vec   % See code in m_vec.m for details

9. Zoom in on Prince Edward Island to show different coastline resolutions

% Example showing the default coastline and all of the different resolutions 
% of GSHHS coastlines as we zoom in on a section of Prince Edward Island.

axes('position',[.35 .6 .37 .37]);
m_proj('albers equal-area','lat',[40 60],'long',[-90 -50],'rect','on');
m_coast('patch',[0 1 0]);
m_text(-69,41,'Standard coastline','color','r','fontweight','bold');

axes('position',[.09 .5 .37 .37]);
m_proj('albers equal-area','lat',[40 54],'long',[-80 -55],'rect','on');
m_gshhs_c('patch',[.2 .8 .2]);
m_text(-80,52.5,'GSHHS\_C (crude)','color','m','fontweight','bold','fontsize',14);

axes('position',[.13 .2 .37 .37]);
m_proj('albers equal-area','lat',[43 48],'long',[-67 -59],'rect','on');
m_gshhs_l('patch',[.4 .6 .4]);
m_text(-66.5,43.5,'GSHHS\_L (low)','color','m','fontweight','bold','fontsize',14);

axes('position',[.35 .05 .37 .37]);
m_proj('albers equal-area','lat',[45.8 47.2],'long',[-64.5 -62],'rect','on');
m_gshhs_i('patch',[.5 .6 .5]);
m_text(-64.4,45.9,'GSHHS\_I (intermediate)','color','m','fontweight','bold','fontsize',14);

axes('position',[.55 .23 .37 .37]);
m_proj('albers equal-area','lat',[46.375 46.6],'long',[-64.2 -63.7],'rect','on');
m_gshhs_h('patch',[.6 .6 .6]);
m_text(-64.18,46.58,'GSHHS\_H (high)','color','m','fontweight','bold','fontsize',14);

10. Tracklines and UTM projection

m_proj('UTM','long',[-72 -68],'lat',[40 44]);

% fake up a trackline


11. Range rings

    xlabel('1000km range rings from Bangkok');

12. Speckled boundary

    bndry_lon=[-128.8 -128.8 -128.3 -128 -126.8 -126.6 -128.8];
    bndry_lat=[49      50.33  50.33  50   49.5   49     49];
    m_proj('lambert','long',[-130 -121.5],'lat',[47 51.5],'rectbox','on');

    m_gshhs_i('color','k');              % Coastline...
    m_gshhs_i('speckle','color','k');    % with speckle added

    m_line(bndry_lon,bndry_lat,'linewi',2,'color','k');     % Area outline ...
    m_hatch(bndry_lon,bndry_lat,'single',30,5,'color','k'); % ...with hatching added.

    title('Speckled Boundaries for nice B&W presentation (best in postscript format)','fontsize',14);

13. Blue Ocean

    m_proj('miller','lat',[-75 75]);  
m_coast('patch',[.7 1 .7],'edgecolor','none');
m_grid('box','fancy','linestyle','none','backcolor',[.9 .99 1]);

cities={'Cairo','Washington','Buenos Aires'};
lons=[ 30+2/60 -77-2/60 -58-22/60];
lats=[ 31+21/60 38+53/60 -34-45/60];

for k=1:3,
[range,ln,lt]=m_lldist([-123-6/60 lons(k)],[49+13/60 lats(k)],40);
m_text(ln(end),lt(end),sprintf('%s - %d km',cities{k},round(range)));

title('Great Circle Routes','fontsize',14,'fontweight','bold');

Examples of satellite data manipulation

1. Global SST (or any variable on a global Lat/Long grid)

% NOAA/NASA Pathfinder AVHRR SST product
% http://podaac.jpl.nasa.gov/sst/


% Documentation for the 54km dataset gives
% this formula for temperature
P=0.15*double(P)-3; % deg C

%...and defines this Lat/Long grid for the data

% Since the grid is rectangluar in lat/long (i.e. not
% really a projection at all, although it is included in
% m_map under the name 'equidistant cyldindrical'), we
% don't want to use the 'image' technique. Instead...
% Create a grid, offsetting by half a grid point to account
% for the flat pcolor


% Rather than rearranging the data so its limits match the
% plot I just draw it twice (you can see the join at 180W
% because of the quirks of flat pcolor) (Note that
% all the global projections have 360 deg ambiguities)
m_pcolor(Plg,Plt,P);shading flat;colormap(map);
hold on;
m_pcolor(Plg-360,Plt,P);shading flat;colormap(map);

m_coast('patch',[.6 1 .6]);

% add a standard colorbar.
set(get(h,'title'),'string','AVHRR SST Nov 1999');
SST pic

2.  SSM/I Ice cover (data provided on a fixed grid)

% SSM/I Ice concentration grids
% (National Snow and Ice Data Center)

P=hdfread('/mnt/cdrom/nasateam/northern/1991/feb/910222.tot','8-bit Raster Image #2');
P(P==168)=101; % Land, no coverage.
P(P==157)=102; % Bad data

% SSM/I ice products are in a polar stereographic projection.
% and the corner points of the grid are given. Here we just
% use those given corner points and 'assume' everything will
% work. It's not bad, although their projection actually uses
% an ellipsoidal earth (m_map uses a spherical earth).


% Convert bottom and left corner points to screen coords. This
% is of course a kludge.
[MAPX,dm]=m_ll2xy([279.26 350.03],[33.92 34.35],'clip','off');
[dm,MAPY]=m_ll2xy([168.35 279.26],[30.98 33.92],'clip','off');

% Plot data as an image
colormap([jet(100);0 0 0;1 1 1]);

m_coast('patch',[.6 .6 .6]);
title('SSM/I Ice cover Feb 22 1991','fontsize',14,'fontweight','bold');

set(get(h,'ylabel'),'string','Total Ice Concentration (%)');

SSMi Ice

3.  Aerial photos on an UTM grid

% This image comes from the TerraServer
% (http://terraserver.microsoft.com/)
% and has been georeferenced to UTM coords. The UTM projection
% uses UTM coordinates on the screen (as long as the ellipse
% parameter is set to something other than the default).

% Set the projection limits to the lat/long of image
% corners.
m_proj('UTM','long',[-71-6/60-30/3600 -71-4/60-43/3600],...
              'lat',[42+21/60+13/3600  42+22/60+7/3600],'ellipse','wgs84');

image([326400 328800],[4692800 4691200],P);set(gca,'ydir','normal');
title('A home for certain nerds','fontsize',16);

4.  A subset of a global dataset (HDF format)

% Ocean colour data from http://seawifs.gsfc.nasa.gov/SEAWIFS.html
% Take a 4km weakly average dataset and plot a map for the Strait of
% Georgia and outer coast. Note that most of this code is used
% for reading in and subsetting the data.

LATLIMS=[47 51];
LONLIMS=[-130 -121];

% Note - This is probably not the most efficient way to read and
%        handle HDF data, but I don't usually do this...
% First, get the attribute data
% And write it into a structure
for k=1:59,
  nm=PI.Attributes(k).Name;nm(nm==' ')='_';
  if isstr(PI.Attributes(k).Value),

% lon/lat of grid corners

% Get the indices needed for the area of interest

% load the subset of data needed for the map limits given
P=hdfread('A20040972004104.L3m_8D_CHLO_4KM','l3m_data','Index',{[ilt ilg],[],[ltlm lglm]});

% Convert data into log(Chla) using the equations given. Blank no-data.
P=(pin.Slope*P+pin.Intercept);   % log_10 of chla


% Draw the map...

m_pcolor(Plg,Plt,P);shading flat;
set(get(h,'ylabel'),'String','Chla (\mug/l)');
set(h,'ytick',log10([.5 1 2 3 5 10 20 30]),'yticklabel',[.5 1 2 3 5 10 20 30],'tickdir','out');
title(['MODIS Chla   ' datestr(datenum(pin.Period_Start_Year,1,0)+pin.Period_Start_Day) ' -> ' ...


Last changed 24/Oct/2014. Questions and comments to rich@eos.ubc.ca